N-Dqn: Neutrosophic Deep Q-Network For Uncertainty-Aware Forecasting And Decision Optimization, Rania Lutfi

Neutrosophic Systems with Applications

Uncertainty remains a critical challenge in dynamic spatiotemporal forecasting. This study proposes the Neutrosophic Deep Q-Network (N-DQN), a framework that integrates neutrosophic logic with deep reinforcement learning to enhance decision optimization under uncertainty. Features are modeled through truth, indeterminacy, and falsity membership functions, enabling robust handling of ambiguous data. The framework incorporates attention-guided preprocessing and horizon-aware optimization to adapt predictions across short- and long-term intervals. Experiments on benchmark traffic datasets (METR-LA and PEMS-BAY) demonstrate improved forecasting accuracy and reduced error rates compared with established baselines. The results highlight the scalability and resilience of N-DQN, positioning it as a promising approach …

Neutrosophic Finsler–Cohomological Framework For Engineering Systems Under Uncertainty, Mona Gharib, Ghulam Muhammad, Muhammad Idrees, Zeeshan Gul

Neutrosophic Systems with Applications

This paper introduces a novel mathematical framework that combines Neutrosophic Finsler Geometry with Neutrosophic Cohomology for evaluating the performance of Brushless Direct Current (BLDC) motors under uncertain and indeterminate operating conditions. Classical motor performance models typically assume precise measurements of torque, current, and efficiency; however, in real-world settings, these parameters are often affected by noise, incomplete information, and conflicting observations. By embedding motor operating states into a neutrosophic Finsler space, the proposed approach captures variations not only in magnitude but also in direction, uncertainty, and conflict of performance metrics. In addition, neutrosophic Cohomology is employed to characterize global invariants of …

Current Research Progress On Electrode Materials For All-Vanadium Redox Flow Batteries, Wen-Qi Wang, Jie Jin, Li-Min Wang, Xin-Yue Liu, Tao Cheng, Yong Hou, Han Xue, Zhi-Yu Wang, Bo Liu, Jia-Bao Liu, Xu-Bin Lu

Journal of Electrochemistry

The redox active species in all-vanadium redox flow batteries (VRFBs) reside in the electrolyte, while the heterogeneous reactions occur on the electrode surface; the electrode is therefore the decisive platform for dynamic adsorption, electron transfer, and ion conversion, especially for the VO²⁺/VO₂⁺ and V²⁺/V³⁺ couples. One of the major challenges for VRFBs is the slow charge transfer in VO²⁺/VO₂⁺ and V²⁺/V³⁺ reactions, mainly caused by poor catalytic performance of electrodes and weak adhesion of catalysts to electrodes. This review focuses on the key challenges and recent …

Triphenylmethane-Derived Levelers For High-Speed Redistribution Layer Copper Electroplating Of Tailored Surface Morphologies, Zi-Hao Song, Wei-Bin Wang, Xiao-Hui Liu, Xiao-Min Han, Yi Zhou, Rui Huang, Yan-Xia Jiang, Zhe Li, Xiao-Wei Liu, Mei-Ling Xiao, Hong-Gang Liao, Wei-Lin Xu, Rong Sun

Journal of Electrochemistry

Redistribution Layer (RDL), composed of layered dielectrics and electroplated copper materials, is a basic structure to rearrange numerous I/O pads on the chip surface in wafer-level advanced packaging. As the key chemicals in electrolyte baths, electroplating additives have undergone continuous development to meet the industrial needs for high-speed and fine-line/fine-pitch applications. Meanwhile, the intricate relationships between additive chemical structures and electroplated copper properties are yet to be well understood. In this work, a pair of triphenylmethane-based dye molecules, i.e., gentian violet (GV) and methyl green (MG), was comparatively investigated as levelers for high-speed RDL copper electroplating. Compared to GV, significantly …

Control Of Pore Nucleation And Rearrangement Kinetics During Aluminium Anodizing In Phosphoric Acid Electrolyte, Ilya V. Roslyakov, Nikita A. Shirin, Dmitry M. Tsymbarenko, Sergei N. Pavlov, Sergey E. Kushnir, Nikolay V. Lyskov, Kirill S. Napolskii

Journal of Electrochemistry

Anodic aluminium oxide (AAO) porous films with an interpore distance of several hundred nanometers are of great interest due to their unique interaction with visible and near-infrared light, and high thermal stability up to 1500 °C. These porous films are prepared by aluminium anodizing at high voltages in weak acids, leading to a slow kinetics of initial stages of porous structure formation. Here, we propose an approach to accelerate AAO formation in electrolytes based on weak acids such as phosphoric acid. Aluminium foils, pre-patterned using first anodizing under different conditions and subsequent selective dissolution of a sacrificial AAO layer, were …

Evaluating Domains' Trustworthiness Based On Uncertainty-Driven Methodologies In The Era Of Sixth Generation, Zekra Sakr, Mona Mohamed

Neutrosophic Systems with Applications

The onset of today's innovations pledges to have a beneficial influence on contemporary civilization in an era of intelligent revolutions, setting a precedent for unrivaled efficiency, creativity, and connectedness. The integration between these technologies contributes to the mutual benefit of each one, wherein this relation is a so-called ``reciprocal partnership''. For instance, the sixth generation (6G) wireless networks permit blockchain nodes to coordinate huge volumes of transaction data in real-time. On the other hand, blockchain is considered a secure valve because spectrum sharing can be automated with blockchain and smart contracts. Accordingly, analyzing and evaluating the contribution of these technologies …

An Uncertainty-Aware Entropy-Oreste Framework For Big Data Platform Selection In Complex Multi-Sector Environments, Ahmed M. Ali, Ibrahim Alrashdi, Karam M. Sallam

Neutrosophic Systems with Applications

The increasing reliance on Big Data platforms across various industries has necessitated the development of systematic decision-support frameworks to guide their evaluation and selection. Given the diversity of available platforms, each offering different capabilities, scalability, and computational efficiency, choosing the optimal solution remains a complex challenge. This research proposes a novel analytical framework that integrates Spherical Fuzzy Sets (SFS) with the Entropy and ORESTE methods to address uncertainty and enhance the accuracy and robustness of Big Data platform evaluation. This hybrid integration, not previously applied to Big Data platform selection, enables objective criteria weighting through the Entropy method and comprehensive …

An Electrochemiluminescence-Based Arsenic (Iii) Sensor Using Luminol On Screen-Printed Gold Electrodes, Harmesa Harmesa, Isnaini Rahmawati, Andrea Fiorani, Yasuaki Einaga, Eny Kusrini, A’An Johan Wahyudi, Asep Saefumillah, Tribidasari A Ivandini

Journal of Electrochemistry

Electrochemiluminescence (ECL) of luminol has been studied on a screen-printed gold electrode for a simple and sensitive detection of arsenic ions (As(III)). Cyclic voltammetry (CV) was applied as the proposed technique to study luminol’s electrochemical behavior and to evaluate the arsenic’s effect in the ECL system, while hydrogen peroxide (H₂O₂) served as a co-reactant to enhance luminol’s light emission under alkaline conditions. To achieve optimal electrode performance, key parameters including pH, scan rate, and the concentrations of H₂O₂ and luminol were carefully optimized. The presence of As(III) induced a quenching effect on the …

Balancing Carbon Emissions In Façade Of Residential Buildings Through Bim-Lca: A Comparative Analysis Of Insulation Materials, Mehran Alipour

Journal of Sustainable Construction Materials and Technologies

Thermal insulation materials play a significant role in balancing buildings' total carbon emissions. Balancing involves applying the optimized amount of insulation materials to avoid excessive emissions in either the operational or embodied phases. Due to the wide range of insulation materials and variations of their specifications, it is vital to analyse them individually. The focus of this study is to optimize the amount of insulation materials in the facades of Residential Buildings (RB) to balance the amount of Operational Carbon Emissions (OCE) and Embodied Carbon Emissions (ECE) by applying the Building Information Modelling-Life Cycle Assessment (BIM-LCA) integration method. The Life …

Evaluating Regularized Logistic Regression And K-Nn On Mnist Under Increasing Random Missingness, Daniel Markwei

Data Science and Data Mining

This paper investigates the effect of random missingness on the performance of regularized multinomial logistic regression and the k-nearest neighbors (k-NN) classifier for handwritten digit recognition on the MNIST dataset. In particular, we study L1-regularized (LASSO) logistic regression and L2-regularized (Ridge) logistic regression alongside k-NN. Varying percentages of random missingness were introduced into the original dataset, and each model was evaluated in terms of its classification performance. The results show that random missingness degrades the performance of all three classifiers. Overall, k-NN consistently achieves higher accuracy than both L1- and L2-regularized logistic regression across all missingness levels; however, its performance …

Nanoscale Opportunities In Extracellular Matrix Mimicry, L. Andrew Lyon, Abbygail Caine, Elif Narbay, E. Daniel Cárdenas-Vásquez

Engineering Faculty Articles and Research

We present an overview of the composition, function, energetics, and dynamics of extracellular matrix and its relation to nanoscale structures and phenomena. These concepts are then related to the development of synthetic and biosynthetic materials that aim to mimic the extracellular matrix for regenerative medicine and tissue engineering technologies. Notable successes and advancements towards the goal of biomimicry are outlined, while remaining challenges and knowledge gaps towards that goal are highlighted. Finally, we frame the remaining challenges in the field in terms of nanoscience-related research opportunities that if solved, might prove to be transformative steps forward in the discipline.

Chapter 6 - Robust Stabilization Ellipsoidal Design For Normal And Contingency Operated Power Systems Using Markov Jump, Ehab Bayoumi

Mechanical Engineering

No abstract provided.

Renewable Microgrid Frequency Regulation Using Active Disturbance Rejection Control And Elephant Herding Optimization, Ehab Bayoumi

Mechanical Engineering

settings Order Article Reprints Open AccessArticle

Renewable Microgrid Frequency Regulation Using Active Disturbance Rejection Control and Elephant Herding Optimization

Design And Control Of A Multi-Modal Electromagnetic Floor Array For Foot-Based Human Locomotion And Stabilization In Microgravity, Aryan Anand

Electrical Engineering Theses

Long-duration living and working in microgravity creates everyday mobility problems such as drifting, loss of stable footing, higher effort to move, and difficulty doing routine tasks safely. Many solutions have been proposed in literature, including handrails, restraint systems, and concepts for artificial gravity using rotation. Artificial gravity could improve comfort, but it is complex to build and operate for large spacecraft, especially when future missions may include not only trained astronauts but also common people. With companies like SpaceX pushing toward large-scale travel and long-term settlement goals, there is a need for simpler mobility support technologies that can work inside …

A Pathfinder Lunar Construction Mission Concept Using Regolith Filled Bags, Cameron S. Dickinson, Fu Nan Shi, Ketan Vasudeva, Rudranarayan M. Mukherjee, Joshua Blanchard, Steve Dubrule, Paul Van Susante, Et Al.

Michigan Tech Publications

Two challenges that have a permanent presence on the Moon are solar and cosmic radiation, as well as the large surface temperature variation between lunar day and night. To address these problems, we propose a lunar pathfinder mission concept that uses robotic systems to investigate whether regolith-filled bags can be used as a versatile construction medium for lunar surface structures and sensors to obtain data on the lunar regolith. The primary objectives of this mission are as follows: evaluation of the surface and subsurface regolith as fill material, lunar excavation using a robotic manipulator equipped with a bucket scoop, bag …

Rapid-Response Reconnaissance Architecture Design For Planetary Defense With Nested Trajectory Optimization, Adam P. Wilmer, Justin A. Atchison, Marcus J. Holzinger, Robert A. Bettinger

Faculty Publications

Reconnaissance is a vital component in a comprehensive planetary defense mitigation strategy—aimed at preventing or reducing the impact threat posed by celestial objects on close-approach trajectories to Earth. It provides decision-makers with critical information on the physical and orbital properties of a near-Earth object (NEO), enabling better assessment of size, composition, and trajectory. This study investigates how to optimally pre-position a fleet of reconnaissance spacecraft prior to the discovery of a specific hazardous NEO. It evaluates response timelines and mission success rates for combinations of spacecraft launched from Earth and those maneuvering from pre-deployed locations within the Sun-Earth system. A …

Machine Learning–Driven Prediction Of Dementia From Mri And Clinical Features: A Comparative Analysis Of Ensemble And Baseline Models, Sarah Raad Hameed, Zainab Muhannad Nahid, Rawan Ahmed Abdulmahdi

AUIQ Technical Engineering Science

Early detection of dementia remains a pressing challenge in clinical neuroscience, as delayed diagnosis limits therapeutic impact and healthcare planning. Leveraging the Open Access Series of Imaging Studies (OASIS) cross-sectional dataset of 436 participants, this study developed a robust machine learning pipeline integrating sociodemographic, clinical, and neuroimaging-derived features. Preprocessing included removal of highly sparse variables (Delay), median imputation of partially missing but clinically essential measures (SES, MMSE, CDR, Educ), Winsorization of extreme values, and skewness correction. The target Clinical Dementia Rating (CDR) was binarized (0 = no dementia, ≥ 0.5 = dementia) to align with clinically actionable screening. Categorical features …

Integrating Sustainable Material Procurement In Construction Waste Management: A Systematic Review With Narrative Synthesis For The Libyan Construction Sector, Ramzi Fouzi Hamad Abdullah, Safaa N Saud Al-Humairi, Zunirah Binti Mohd Talib

Journal of Sustainable Construction Materials and Technologies

Integrating sustainable material procurement with construction waste management is essential to reduce construction and demolition waste in Libya, where current practices remain largely reactive and disposal-oriented. This narrative review aims to develop a conceptual framework linking procurement decisions to waste-generation pathways in Libyan construction projects, clarifying how proactive, sustainability-driven purchasing can serve as a primary driver of waste prevention. Using a PRISMA-guided systematic search of Web of Science, Scopus, and IEEE Xplore for 2001–2026, and a bibliometric analysis via VOSviewer, 956 high-quality studies were synthesized to map global knowledge and to expose the paucity of integrated SMP–CWM studies in developing …

Sound Insulation Performance Of Sustainable Lc3 Mortars With Barite And Waste Rubber Aggregates, Begüm Söyek Abay, Leyla Tanaçan

Journal of Sustainable Construction Materials and Technologies

This study investigates the potential of limestone calcined clay cement (LC3) as a sustainable binder for developing a single-layer composite material incorporating barite and rubber aggregates, hypothesized to achieve enhanced sound insulation performance compared to conventional multi-layered wall systems. Mortars were prepared using LC3 with 55% clinker, 30% metakaolin, 15% limestone, substituting 45% of cement clinker. Hybrid mixtures of barite and rubber aggregates (barite-to-rubber volume ratios of 2:1 and 1:2) were tested at aggregate-to-binder ratios of 2.0, 2.75, and 3.5 to evaluate their combined mass and damping effects on acoustic performance. Experiments were conducted to determine physical, mechanical, and acoustic …

From Lime To Geopolymers: Emerging Trends And Advances In Sustainable Soil Stabilization, Favour Chukwuebuka Egwu, Amin Eisazadeh

Journal of Sustainable Construction Materials and Technologies

Soil stabilization remains a critical challenge in geotechnical engineering, particularly for weak and expansive soils that compromise the safety and serviceability of infrastructure. Traditional stabilizers such as lime and cement have been widely applied; however, their limitations in terms of long-term durability, carbon footprint, and performance under aggressive environmental conditions necessitate alternative approaches. In recent years, geopolymer-based stabilizers derived from industrial by-products such as fly ash (FA), slag, and bottom ash (BA) have emerged as promising substitutes. This review critically examines the comparative performance of lime and geopolymer stabilization with respect to strength development, durability, compressibility, environmental impact, and economic …

Investigating The Behavior Of Self-Compacting Concrete Containing Scms And Recycled Fine Aggregates, Sachin Tiwari, Mahakavi P

Journal of Sustainable Construction Materials and Technologies

This study addresses the unresolved gap in quantifying how recycled fine aggregates (RFA) and metakaolin (MK) interact synergistically in self-compacting concrete (SCC), a relationship that previous works have studied only in isolation or without mechanistic justification. Twenty-five SCC mixtures containing MK (0–25%) and RFA (0–100%) were evaluated to generate a unified understanding of fresh behaviour, strength development, pore refinement, interfacial transition zone (ITZ) characteristics, and sustainability indicators. Results show that RFA alone increases water demand and reduces strength, while MK compensates for these losses by densifying the matrix and improving ITZ bonding, as confirmed through SEM analysis. An optimum synergy …

Improving The Uv Resistance And Service Life Of Polystyrene-Based Building Materials Via Low-Concentration Metal Complex Modifiers, Dina S. Ahmed, Marwa Fadhil, Raghda Alsayed, Mohammed Kadhom, Muna Bufaroosha, Amani Husain, Thura Alyasiri, Hanan Ibraheem, Alaa A. Rashad, Bassam M. Abood, Riyadh Noaman, Ahmed Ahmed, Ruqaya Raad, Ala'a Shaker, Abeer Erfan, Hassan Hashim, Saba Hamza, Rahimi M. Yusop, Emad Yousif

AUIQ Technical Engineering Science

PS is highly susceptible to UV-induced photodegradation, which results in deterioration of its mechanical and aesthetic properties. In the present study, four novel and highly aromatic levofloxacin metal complexes, synthesized from Zn, Sn, Cu, and Ni, were investigated as low-concentration (0.5% w/w) photostabilizer additives for PS. Composite films were prepared by solution casting and subjected to accelerated UV irradiation up to 300 hours. Photostabilizing performance was systematically followed by monitoring changes in the carbonyl index via FT-IR spectroscopy, mass loss measurements, and surface morphology analyses using SEM and AFM. Results showed that all levofloxacin metal complexes had a pronounced inhibition …

Nanoparticles May Improve How Antiviral Compounds Are Delivered For Herpes Virus 1, Emilia Huff

Research on Capitol Hill

HSV-1, a strain of herpes, infects the majority of adults in the US and has been linked to neurological damage.

Utah’S Waste Glass Makes Concrete Stronger And Improves Durability, Rosemary Yahne

Research on Capitol Hill

Utah landfills receive thousands of tons of waste glass annually while our concrete industry relies on cement, one of the world's largest sources of CO₂ emissions.

We discovered that finely ground recycled glass can replace up to 30% of cement in concrete and improve performance.

This research tests whether Utah's waste-recycled glass can create stronger, more durable concrete for our roads, bridges, and buildings.

Rapid Single-Cell Measurement Of Transient Transmembrane Water Flow Under Osmotic Gradient, Hong Jiang, Jinnawat Jongkhumkrong, Y. J. Chao, Qian Wang, Guiren Wang

Faculty Publications

Aquaporins (AQPs) are critical for transmembrane water transport in response to osmotic gradients, but their gating and regulatory mechanisms remain poorly understood. A central challenge is the lack of methods to measure water flow across AQPs from individual cells with the spatiotemporal resolution and sensitivity equivalent to patch-clamp recordings of ion fluxes—a limitation stemming from the electrically silent nature of water flow. Here, we present a novel optical technique—Flow-Induced Fluorescence Increase Velocimetry (FIFIV) based on Laser-Induced Fluorescence Photobleaching Anemometry (LIFPA)—that enables direct, real-time monitoring of cytoplasmic flow induced by transmembrane water transport under osmotic pressure gradients. Using small molecular fluorescent …

Discovery Of Dynamical Structures Mapping Chaotic Transport Pathways In The Earth–Moon Cr3bp, Tyler J. Kapolka, Christina E. Paljug, Robert A. Bettinger, Rachel Oliver, Bruce A. Cox, Jeremiah A. Specht

Faculty Publications

Chaos; Deterministic chaos; Earth–Moon system; Poincaré map; Quasi-chaotic; Surface of section /// For the Circular Restricted 3-Body Problem (CR3BP), the topologies present within a Poincaré map enable the extraction of useful information regarding periodic, quasi-periodic, and chaotic trajectory behavior. Aside from the prominent topologies that follow distinct concentric patterns around fixed points, indicative of the periodic and quasi-periodic motion that is often the central focus of CR3BP research, there are also many “dusty” regions on the Poincaré map that appear random without an apparent structure and are indicative of chaotic motion. This paper, for the first time in literature, identifies …

Mae Enewsbrief Oct-Dec 2025, Department Of Mechanical And Aerospace Engineering, Michigan Technological University

Department of Mechanical and Aerospace Engineering eNewsBrief

No abstract provided.

Remote Sensing Of Dynamic Ground Motion Via A Moiré-Based Apparatus, Adrian Ali Moazzam, Nontawat Srisapan, Gregory Waite, Durdu Guney, Roohollah Askari

Michigan Tech Publications

Highlights: What are the main findings? A Moiré-based optical apparatus enables long-range, non-contact ground displacement measurement in hazardous environments. Controlled indoor and outdoor experiments demonstrate reliable detection of dynamic and seismic-like ground motions with sub-millimeter resolution. What are the implications of the main findings? System performance is evaluated under atmospheric turbulence and wind, revealing key limits and mitigation strategies for field deployment. The proposed approach provides a low-cost, scalable complement to traditional seismic and geodetic monitoring techniques. Ground-based remote sensing of seismic and geophysical displacements remains a major challenge due to environmental hazards, signal attenuation, and practical deployment limitations of …

Advances In Real-Time American Sign Language Recognition System Using Deep Learning Techniques For Enhanced Accessibility, Bader Alsharif

Electronic Theses and Dissertations 2020 - Present

Advancements in technology have significantly contributed to the development of innovative tools aimed at improving communication and accessibility for individuals with hearing impairments. This dissertation explores various machine learning and deep learning techniques for recognizing American Sign Language (ASL) gestures, focusing on enhancing accessibility and bridging the communication gap between hearing-impaired and hearing individuals. Traditional machine learning models, such as Random Forest, Support Vector Machines (SVM), and K-Nearest Neighbors (KNN), alongside deep learning architectures like AlexNet, ResNet-50, EfficientNet, ConvNeXt, and VisionTransformer, were investigated for their effectiveness. Experiments conducted on an extensive dataset of 87,000 ASL gesture images revealed exceptional recognition …

Machine Learning For Elderly Behavior And Risk Incident Modeling, Muhammad Tanveer Jan

Electronic Theses and Dissertations 2020 - Present

The rapid expansion of the aging population presents critical challenges to healthcare systems, particularly in maintaining independent living, ensuring mobility safety, and optimizing emergency interventions. Traditional monitoring solutions are often fragmented, reactive, and hindered by the scarcity of data regarding rare high-risk events. This dissertation proposes a comprehensive, multi-modal machine learning framework designed to model elderly behavior and predict risk incidents across three critical environments: the home, the vehicle, and the clinical setting.

To address the fundamental challenge of class imbalance in medical and behavioral datasets—where risk events are statistically rare—this research first introduces a dual-phase data augmentation strategy. By …